I'm attempting to build a ROM-based Window function using DSPComplex and FixedPoint types, but seem to keep running into the following error:
chisel3.core.Binding$ExpectedHardwareException: vec element 'dsptools.numbers.DspComplex#32' must be hardware, not a bare Chisel type
The source code for my attempt at this looks like the following:
class TaylorWindow(len: Int, window: Seq[FixedPoint]) extends Module {
val io = IO(new Bundle {
val d_valid_in = Input(Bool())
val sample = Input(DspComplex(FixedPoint(16.W, 8.BP), FixedPoint(16.W, 8.BP)))
val windowed_sample = Output(DspComplex(FixedPoint(24.W, 8.BP), FixedPoint(24.W, 8.BP)))
val d_valid_out = Output(Bool())
})
val win_coeff = Vec(window.map(x=>DspComplex(x, FixedPoint(0, 16.W, 8.BP))).toSeq) // ROM storing our coefficients.
io.d_valid_out := io.d_valid_in
val counter = Reg(UInt(10.W))
// Implicit reset
io.windowed_sample:= io.sample * win_coeff(counter)
when(io.d_valid_in) {
counter := counter + 1.U
}
}
println(getVerilog(new TaylorWindow(1024, fp_seq)))
I'm actually reading the coefficients in from a file (this particular window has a complex generation function that I'm doing in Python elsewhere) with the following sequence of steps
val filename = "../generated/taylor_coeffs"
val coeff_file = Source.fromFile(filename).getLines
val double_coeffs = coeff_file.map(x => x.toDouble)
val fp_coeffs = double_coeffs.map(x => FixedPoint.fromDouble(x, 16.W, 8.BP))
val fp_seq = fp_coeffs.toSeq
Does this mean the DSPComplex type isn't able to be translated to Verilog?
Commenting out the win_coeff line seems to make the whole thing generate (but clearly doesn't do what I want it to do)
I think you should try using
val win_coeff = VecInit(window.map(x=>DspComplex.wire(x, FixedPoint.fromDouble(0.0, 16.W, 8.BP))).toSeq) // ROM storing our coefficients.
which will create hardware values like you want. The Vec just creates a Vec of the type specfied
Related
I have a sequence of values that I know at compile-time, for example: const x: seq[string] = #["s1", "s2", "s3"]
I want to loop over that seq in a manner that keeps the variable a static string instead of a string as I intend to use these strings with macros later.
I can iterate on objects in such a manner using the fieldPairs iterator, but how can I do the same with just a seq?
A normal loop such as
for s in x:
echo s is static string
does not work, as s will be a string, which is not what I need.
The folks over at the nim forum were very helpful (here the thread).
The solution appears to be writing your own macro to do this. 2 solutions I managed to make work for me were from the users mratsim and a specialized version from hlaaftana
Hlaaftana's version:
This one unrolls the loop over the various values in the sequence. By that I mean, that the "iterating variable s" changes its value and is always the value of one of the entries of that compile-time seq x (or in this example a). In that way it functions basically like a normal for-in loop.
import macros
macro unrollSeq(x: static seq[string], name, body: untyped) =
result = newStmtList()
for a in x:
result.add(newBlockStmt(newStmtList(
newConstStmt(name, newLit(a)),
copy body
)))
const a = #["la", "le", "li", "lo", "lu"]
unrollSeq(a, s):
echo s is static
echo s
mratsim's version:
This one doesn't unroll a loop over the values, but over a range of indices.
You basically tell the staticFor macro over what range of values you want an unrolled for loop and it generates that for you. You can access the individual entries in the seq then with that index.
import std/macros
proc replaceNodes(ast: NimNode, what: NimNode, by: NimNode): NimNode =
# Replace "what" ident node by "by"
proc inspect(node: NimNode): NimNode =
case node.kind:
of {nnkIdent, nnkSym}:
if node.eqIdent(what):
return by
return node
of nnkEmpty:
return node
of nnkLiterals:
return node
else:
var rTree = node.kind.newTree()
for child in node:
rTree.add inspect(child)
return rTree
result = inspect(ast)
macro staticFor*(idx: untyped{nkIdent}, start, stopEx: static int, body: untyped): untyped =
result = newStmtList()
for i in start .. stopEx: # Slight modification here to make indexing behave more in line with the rest of nim-lang
result.add nnkBlockStmt.newTree(
ident("unrolledIter_" & $idx & $i),
body.replaceNodes(idx, newLit i)
)
staticFor(index, x.low, x.high):
echo index
echo x[index] is static string
Elegantbeefs version
Similar to Hlaaftana's version this unrolls the loop itself and provides you a value, not an index.
import std/[macros, typetraits]
proc replaceAll(body, name, wth: NimNode) =
for i, x in body:
if x.kind == nnkIdent and name.eqIdent x:
body[i] = wth
else:
x.replaceAll(name, wth)
template unrolledFor*(nameP, toUnroll, bodyP: untyped): untyped =
mixin
getType,
newTree,
NimNodeKind,
`[]`,
add,
newIdentDefs,
newEmptyNode,
newStmtList,
newLit,
replaceAll,
copyNimTree
macro myInnerMacro(name, body: untyped) {.gensym.} =
let typ = getType(typeof(toUnroll))
result = nnkBlockStmt.newTree(newEmptyNode(), newStmtList())
result[^1].add nnkVarSection.newTree(newIdentDefs(name, typ[^1]))
for x in toUnroll:
let myBody = body.copyNimTree()
myBody.replaceAll(name, newLit(x))
result[^1].add myBody
myInnerMacro(nameP, bodyP)
const x = #["la", "le", "Li"]
unrolledFor(value, x):
echo value is static
echo value
All of them are valid approaches.
I store various formulas in Postgres and I want to use those formulas in my code. It would look something like this:
var amount = 100;
var formula = '5/105'; // normally something I would fetch from Postgres
var total = amount * formula; // should return 4.76
Is there a way to evaluate the string in this manner?
As far as I'm aware, there isn't a formula solver package developed for Dart yet. (If one exists or gets created after this post, we can edit it into the answer.)
EDIT: Mattia in the comments points out the math_expressions package, which looks pretty robust and easy to use.
There is a way to execute arbitrary Dart code as a string, but it has several problems. A] It's very roundabout and convoluted; B] it becomes a massive security issue; and C] it only works if the Dart is compiled in JIT mode (so in Flutter this means it will only work in debug builds, not release builds).
So the answer is that unfortunately, you will have to implement it yourself. The good news is that, for simple 4-function arithmetic, this is pretty straight-forward, and you can follow a tutorial on writing a calculator app like this one to see how it's done.
Of course, if all your formulas only contain two terms with an operator between them like in your example snippet, it becomes even easier. You can do the whole thing in just a few lines of code:
void main() {
final amount = 100;
final formula = '5/105';
final pattern = RegExp(r'(\d+)([\/+*-])(\d+)');
final match = pattern.firstMatch(formula);
final value = process(num.parse(match[1]), match[2], num.parse(match[3]));
final total = amount * value;
print(total); // Prints: 4.761904761904762
}
num process(num a, String operator, num b) {
switch (operator) {
case '+': return a + b;
case '-': return a - b;
case '*': return a * b;
case '/': return a / b;
}
throw ArgumentError(operator);
}
There are a few packages that can be used to accomplish this:
pub.dev/packages/function_tree
pub.dev/packages/math_expressions
pub.dev/packages/expressions
I used function_tree as follows:
double amount = 100.55;
String formula = '5/105*.5'; // From Postgres
final tax = amount * formula.interpret();
I haven't tried it, but using math_expressions it should look like this:
double amount = 100.55;
String formula = '5/105*.5'; // From Postgres
Parser p = Parser();
// Context is used to evaluate variables, can be empty in this case.
ContextModel cm = ContextModel();
Expression exp = p.parse(formula) * p.parse(amount.toString());
// or..
//Expression exp = p.parse(formula) * Number(amount);
double result = exp.evaluate(EvaluationType.REAL, cm);
// Result: 2.394047619047619
print('Result: ${result}');
Thanks to fkleon for the math_expressions help.
i am new with f# , will be great if some 1 can help , nearly half a day gone solving this problem Thank you
module Certificate =
type T = {
Id: int
IsECert: bool
IsPrintCert: bool
CertifiedBy: string
Categories: Category.T list
}
let createPending now toZonedDateTime toBeCertifiedByName (job: Models.Job.T) (certificateType: Models.CertificateType.T) (pendingCertificate: Models.PendingCertificate.T) visualization (categories: Category.T list) =
let forCompletion = Models.PendingCertificate.getCertificateForCompletion pendingCertificate
{
Id = forCompletion.Id |> CertificateId.toInt
IsECert = Models.PendingCertificate.isECertificate pendingCertificate
IsPrintCert = Models.PendingCertificate.isPrintCertificate pendingCertificate
CertifiedBy = toBeCertifiedByName
Categories = categories}
i am getting an error in "Incomplete structured construct at or before this point"
Your formatting is all off. I will assume here that this is just a result of posting to StackOverflow, and your actual code is well indented.
The error comes from the definition of createPending: this function does not have a result. All its body consists of defining a forCompletion value, but there is nothing after it. Here's a simpler example that has the same problem:
let f x =
let y = 5
This function will produce the same error, because it also doesn't have a result. In F#, every function has to return something. The body cannot contain only definitions of helper functions or values. For example, I could fix my broken function above like this:
let f x =
let y = 5
x + y
This function first defines a helper value y, then adds it to its argument x, and returns the result.
> f 2
> 7
>
> f 0
> 5
How exactly you need to fix your function depends on what exactly you want it to mean. I can't help you here, because you haven't provided that information.
After investing good amount of searching on net for this topic, I am ending up here if I can get some pointer . please read further
After analyzing Spark 2.0 I concluded polynomial regression is not possible with spark (spark alone), so is there some extension to spark which can be used for polynomial regression?
- Rspark it could be done (but looking for better alternative)
- RFormula in spark does prediction but coefficients are not available (which is my main requirement as I primarily interested in coefficient values)
Polynomial regression is just another case of a linear regression (as in Polynomial regression is linear regression and Polynomial regression). As Spark has a method for linear regression, you can call that method changing the inputs in such a way that the new inputs are the ones suited to polynomial regression. For instance, if you only have one independent variable x, and you want to do quadratic regression, you have to change your independent input matrix for [x x^2].
I would like to add some information to #Mehdi Lamrani’s answer :
If you want to do a polynomial linear regression in SparkML, you may use the class PolynomialExpansion.
For information check the class in the SparkML Doc
or in the Spark API Doc
Here is an implementation example:
Let's assume we have a train and test datasets, stocked in two csv files, with headers containing the neames of the columns (features, label).
Each data set contains three features named f1,f2,f3, each of type Double (this is the X matrix), as well as a label feature (the Y vector) named mylabel.
For this code I used Spark+Scala:
Scala version : 2.12.8
Spark version 2.4.0.
We assume that SparkML library was already downloaded in build.sbt.
First of all, import librairies :
import org.apache.spark.ml.{Pipeline, PipelineModel}
import org.apache.spark.ml.linalg.{Vector, Vectors}
import org.apache.spark.ml.regression.LinearRegression
import org.apache.spark.mllib.evaluation.RegressionMetrics
import org.apache.spark.sql.{DataFrame, SparkSession}
import org.apache.spark.sql.functions.udf
import org.apache.spark.{SparkConf, SparkContext}
Create Spark Session and Spark Context :
val ss = org.apache.spark.sql
.SparkSession.builder()
.master("local")
.appName("Read CSV")
.enableHiveSupport()
.getOrCreate()
val conf = new SparkConf().setAppName("test").setMaster("local[*]")
val sc = new SparkContext(conf)
Instantiate the variables you are going to use :
val f_train:String = "path/to/your/train_file.csv"
val f_test:String = "path/to/your/test_file.csv"
val degree:Int = 3 // Set the degree of your choice
val maxIter:Int = 10 // Set the max number of iterations
val lambda:Double = 0.0 // Set your lambda
val alpha:Double = 0.3 // Set the learning rate
First of all, let's create first several udf-s, which will be used for the data reading and pre-processing.
The arguments' types of the udf toFeatures will be Vector followed by the type of the arguments of the features: (Double,Double,Double)
val toFeatures = udf[Vector, Double, Double, Double] {
(a,b,c) => Vectors.dense(a,b,c)
}
val encodeIntToDouble = udf[Double, Int](_.toDouble)
Now let's create a function which extracts data from CSV and creates, new features from the existing ones, using PolynomialExpansion:
def getDataPolynomial(
currentfile:String,
sc:SparkSession,
sco:SparkContext,
degree:Int
):DataFrame =
{
val df_rough:DataFrame = sc.read
.format("csv")
.option("header", "true") //first line in file has headers
.option("mode", "DROPMALFORMED")
.option("inferSchema", value=true)
.load(currentfile)
.toDF("f1", "f2", "f3", "myLabel")
// you may add or not the last line
val df:DataFrame = df_rough
.withColumn("featNormTemp", toFeatures(df_rough("f1"), df_rough("f2"), df_rough("f3")))
.withColumn("label", Tools.encodeIntToDouble(df_rough("myLabel")))
val polyExpansion = new PolynomialExpansion()
.setInputCol("featNormTemp")
.setOutputCol("polyFeatures")
.setDegree(degree)
val polyDF:DataFrame=polyExpansion.transform(df.select("featNormTemp"))
val datafixedWithFeatures:DataFrame = polyDF.withColumn("features", polyDF("polyFeatures"))
val datafixedWithFeaturesLabel = datafixedWithFeatures
.join(df,df("featNormTemp") === datafixedWithFeatures("featNormTemp"))
.select("label", "polyFeatures")
datafixedWithFeaturesLabel
}
Now, run the function both for the train and test datasets, using the chosen degree for the Polynomial expansion.
val X:DataFrame = getDataPolynomial(f_train,ss,sc,degree)
val X_test:DataFrame = getDataPolynomial(f_test,ss,sc,degree)
Run the algorithm in order to get a model of linear regression, using a pipeline :
val assembler = new VectorAssembler()
.setInputCols(Array("polyFeatures"))
.setOutputCol("features2")
val lr = new LinearRegression()
.setMaxIter(maxIter)
.setRegParam(lambda)
.setElasticNetParam(alpha)
.setFeaturesCol("features2")
.setLabelCol("label")
// Fit the model:
val pipeline:Pipeline = new Pipeline().setStages(Array(assembler,lr))
val lrModel:PipelineModel = pipeline.fit(X)
// Get prediction on the test set :
val result:DataFrame = lrModel.transform(X_test)
Finally, evaluate the result using mean squared error measure :
def leastSquaresError(result:DataFrame):Double = {
val rm:RegressionMetrics = new RegressionMetrics(
result
.select("label","prediction")
.rdd
.map(x => (x(0).asInstanceOf[Double], x(1).asInstanceOf[Double])))
Math.sqrt(rm.meanSquaredError)
}
val error:Double = leastSquaresError(result)
println("Error : "+error)
I hope this might be useful !
I am playing with records and list. Please, I want to know how to use one variable twice. When I assign any values into variable _list and after that I try rewrite this variable then raising error:
** exception error: no match of right hand side value
-module(hello).
-author("anx00040").
-record(car, {evc, type, color}).
-record(person, {name, phone, addresa, rc}).
-record(driver, {rc, evc}).
-record(list, {cars = [], persons = [], drivers = []} ).
%% API
-export([helloIF/1, helloCase/1, helloResult/1, helloList/0, map/2, filter/2, helloListCaA/0, createCar/3, createPerson/4, createDriver/2, helloRecords/0, empty_list/0, any_data/0, del_Person/1, get_persons/1, do_it_hard/0, add_person/2]).
createCar(P_evc, P_type, P_color) -> _car = #car{evc = P_evc, type = P_type, color = P_color}, _car
.
createPerson(P_name, P_phone, P_addres, P_rc) -> _person= #person{name = P_name, phone = P_phone, addresa = P_addres, rc = P_rc}, _person
.
createDriver(P_evc, P_rc) -> _driver = #driver{rc = P_rc, evc = P_evc}, _driver
.
empty_list() ->
#list{}.
any_data() ->
_car1 = hello:createCar("BL 4", "Skoda octavia", "White"),
_person1 = hello:createPerson("Eduard B.","+421 917 111 711","Kr, 81107 Bratislava1", "8811235"),
_driver1 = hello:createDriver(_car1#car.evc, _person1#person.rc),
_car2 = hello:createCar("BL 111 HK", "BMW M1", "Red"),
_person2 = hello:createPerson("Lenka M","+421 917 111 111","Krizn0, 81107 Bratislava1", "8811167695"),
_driver2 = hello:createDriver(_car2#car.evc, _person2#person.rc),
_car3 = hello:createCar("BL 123 AB", "Audi A1 S", "Black"),
_person3 = hello:createPerson("Stela Ba.","+421 918 111 711","Azna 20, 81107 Bratislava1", "8811167695"),
_driver3 = hello:createDriver(_car3#car.evc, _person3#person.rc),
_list = #list{
cars = [_car1,_car2,_car3],
persons = [_person1, _person2, _person3],
drivers = [_driver1, _driver2, _driver3]},
_list.
add_person(List, Person) ->
List#list{persons = lists:append([Person], List#list.persons) }.
get_persons(#list{persons = P}) -> P.
do_it_hard()->
empty_list(),
_list = add_person(any_data(), #person{name = "Test",phone = "+421Test", addresa = "Testova 20 81101 Testovo", rc =88113545}),
io:fwrite("\n"),
get_persons(add_person(_list, #person{name = "Test2",phone = "+421Test2", addresa = "Testova 20 81101 Testovo2", rc =991135455}))
.
But it raising error when i use variable _list twice:
do_it_hard()->
empty_list(),
_list = add_person(any_data(), #person{name = "Test",phone = "+421Test", addresa = "Testova 20 81101 Testovo", rc =88113545}),
_list =add_person(_list, #person{name = "Test2",phone = "+421Test2", addresa = "Testova 20 81101 Testovo2", rc =991135455}),
get_persons(_list)
.
In the REPL, it can be convenient to experiment with things while re-using variable names. There, you can do f(A). to have Erlang "forget" the current assignment of A.
1> Result = connect("goooogle.com").
{error, "server not found"}
2> % oops! I misspelled the server name
2> f(Result).
ok
3> Result = connect("google.com").
{ok, <<"contents of the page">>}
Note that this is only a REPL convenience feature. You can't do this in actual code.
In actual code, variables can only be assigned once. In a procedural language (C, Java, Python, etc), the typical use-case for reassignment is loops:
for (int i = 0; i < max; i++) {
conn = connect(servers[i]);
reply = send_data(conn);
print(reply);
}
In the above, the variables i, conn, and reply are reassigned in each iteration of the loop.
Functional languages use recursion to perform their loops:
send_all(Max, Servers) ->
send_loop(1, Max, Servers).
send_loop(Current, Max, _Servers) when Current =:= Max->
ok;
send_loop(Current, Max, Servers) ->
Conn = connect(lists:nth(Current, Servers)),
Reply = send_data(Conn),
print(Reply).
This isn't very idiomatic Erlang; I'm trying to make it mirror the procedural code above.
As you can see, I'm getting the same effect, but my assignments within a function are fixed.
As a side note, you are using a lot of variable names beginning with underscore. In Erlang this is a way of hinting that you will not be using the value of these variables. (Like in the above example, when I've reached the end of my list, I don't care about the list of servers.) Using a leading underscore as in your code turns off some useful compiler warnings and will confuse any other developers who look at your code.
In some situations it is convenient to use use SeqBind:
SeqBind is a parse transformation that auto-numbers all occurrences of these bindings following the suffix # (creating L#0, L#1, Req#0, Req#1) and so on.
Simple example:
...
-compile({parse_transform,seqbind}).
...
List# = lists:seq(0, 100),
List# = lists:filter(fun (X) -> X rem 2 == 0 end, List#)
...
I used google...
Erlang is a single-assignment language. That is, once a variable has been given a value, it cannot be given a different value. In this sense it is like algebra rather than like most conventional programming languages.
http://www.cis.upenn.edu/~matuszek/General/ConciseGuides/concise-erlang.html